AIMC Topic: Biological Evolution

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Synergetic learning for unknown nonlinear H control using neural networks.

Neural networks : the official journal of the International Neural Network Society Sep 20, 2023
The well-known H control design gives robustness to a controller by rejecting perturbations from the external environment, which is difficult to do for completely unknown affine nonlinear systems. Accordingly, the immediate objective of this paper is...
Biological Evolution Nonlinear Dynamics Neural Networks, Computer Computer Simulation Algorithms
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Harnessing deep learning for population genetic inference.

Nature reviews. Genetics Sep 4, 2023
In population genetics, the emergence of large-scale genomic data for various species and populations has provided new opportunities to understand the evolutionary forces that drive genetic diversity using statistical inference. However, the era of p...
Deep Learning Biological Evolution Genetics, Population Genome Genomics
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Hierarchical growth in neural networks structure: Organizing inputs by Order of Hierarchical Complexity.

PloS one Aug 31, 2023
Several studies demonstrate that the structure of the brain increases in hierarchical complexity throughout development. We tested if the structure of artificial neural networks also increases in hierarchical complexity while learning a developing ta...
Biological Evolution Brain Neural Networks, Computer Computer Simulation Records
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Technology Trends for Massive MIMO towards 6G.

Sensors (Basel, Switzerland) Jun 30, 2023
At the dawn of the next-generation wireless systems and networks, massive multiple-input multiple-output (MIMO) in combination with leading-edge technologies, methodologies, and architectures are poised to be a cornerstone technology. Capitalizing on...
Technology Communication Artificial Intelligence Biological Evolution Intelligence
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The morphological paradigm in robotics.

Studies in history and philosophy of science Jun 2, 2023
In the paper, we are going to show how robotics is undergoing a shift in a bionic direction after a period of emphasis on artificial intelligence and increasing computational efficiency, which included isolation and extreme specialization. We assembl...
Artificial Intelligence Bionics Biological Evolution Robotics
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SVcnn: an accurate deep learning-based method for detecting structural variation based on long-read data.

BMC bioinformatics May 23, 2023
BACKGROUND: Structural variations (SVs) refer to variations in an organism's chromosome structure that exceed a length of 50 base pairs. They play a significant role in genetic diseases and evolutionary mechanisms. While long-read sequencing technolo...
Biological Evolution Deep Learning
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A systematic review of biologically-informed deep learning models for cancer: fundamental trends for encoding and interpreting oncology data.

BMC bioinformatics May 15, 2023
BACKGROUND: There is an increasing interest in the use of Deep Learning (DL) based methods as a supporting analytical framework in oncology. However, most direct applications of DL will deliver models with limited transparency and explainability, whi...
Biology Neoplasms Humans Biological Evolution Deep Learning Medical Oncology
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Jumping over fences: why field- and laboratory-based biomechanical studies can and should learn from each other.

The Journal of experimental biology Apr 20, 2023
Locomotor biomechanics faces a core trade-off between laboratory-based and field-based studies. Laboratory conditions offer control over confounding factors, repeatability, and reduced technological challenges, but limit the diversity of animals and ...
Biomechanical Phenomena Ecology Biological Evolution Locomotion Ecosystem Animals Robotics
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Complex computation from developmental priors.

Nature communications Apr 19, 2023
Machine learning (ML) models have long overlooked innateness: how strong pressures for survival lead to the encoding of complex behaviors in the nascent wiring of a brain. Here, we derive a neurodevelopmental encoding of artificial neural networks th...
Biological Evolution Neurons Machine Learning Neural Networks, Computer Brain
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Major evolutionary transitions in individuality between humans and AI.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences Jan 23, 2023
That humans might undergo future evolutionary transitions in individuality (ETIs) seems fanciful. However, drawing upon recent thinking concerning the origins of properties that underpin ETIs, I argue that certain ETIs are imminently realizable. Cent...
Algorithms Reproduction Artificial Intelligence Symbiosis Humans Biological Evolution
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